Clues to NaCN formation

ALMA is providing us essential information on where certain molecules form. Observing where these molecules emission arises from, the physical conditions of the gas, and how this relates with the presence of other species allows us to understand the formation of many species, and to significantly improve our knowledge of the chemistry that occurs in the space. We studied the molecular distribution of NaCN around IRC +10216, a molecule detected previously, but whose origin is not clear. High angular resolution maps allow us to model the abundance distribution of this molecule and check suggested formation paths. We modeled the emission of NaCN assuming local thermal equilibrium (LTE) conditions. These profiles were fitted to azimuthal averaged intensity profiles to obtain an abundance distribution of NaCN. We found that the presence of NaCN seems compatible with the presence of CN, probably as a result of the photodissociation of HCN, in the inner layers of the ejecta of IRC +10216. However, similar as for CH 3 CN, current photochemical models fail to reproduce this CN reservoir. We also found that the abundance peak of NaCN appears at a radius of 3 x 10 15 cm, approximately where the abundance of NaCl, suggested to be the parent species, starts to decay. However, the abundance ratio shows that the NaCl abundance is lower than that obtained for NaCN. We expect that the LTE assumption might result in NaCN abundances higher than the real ones. Updated photochemical models, collisional rates, and reaction rates are essential to determine the possible paths of the NaCN formation.Comment: 7 pages, 10 figures. Accepted for publication in A&A letter

CdV2O4: A rare example of a collinear multiferroic spinel

By studying the dielectric properties of the geometrically frustrated spinel CdV2O4, we observe ferroelectricity developing at the transition into the collinear antiferromagnetic ground state. In this multiferroic spinel, ferroelectricity is driven by local magnetostriction and not by the more common scenario of spiral magnetism. The experimental findings are corroborated by ab-initio calculations of the electric polarization and the underlying spin and orbital order. The results point towards a charge rearrangement due to dimerization, where electronic correlations and the proximity to the insulator-metal transition play an important role.Comment: 4+ pages, 3 figure

Temperature oscillations of magnetization observed in nanofluid ferromagnetic graphite

We report on unusual magnetic properties observed in the nanofluid room-temperature ferromagnetic graphite (with an average particle size of l=10nm). More precisely, the measured magnetization exhibits a low-temperature anomaly (attributed to manifestation of finite size effects below the quantum temperature) as well as pronounced temperature oscillations above T=50K (attributed to manifestation of the hard-sphere type pair correlations between ferromagnetic particles in the nanofluid)

Manifestation of finite temperature size effects in nanogranular magnetic graphite

In addition to the double phase transition (with the Curie temperatures T_C=300K and T_{Ct}=144K), a low-temperature anomaly in the dependence of the magnetization is observed in the bulk magnetic graphite (with an average granular size of L=10nm), which is attributed to manifestation of the size effects below the quantum temperature. The best fits of the high-temperature data (using the mean-field Curie-Weiss and Bloch expressions) produced reasonable estimates for the model parameters, such as defects mediated effective spin exchange energy J=12meV (which defines the intragranular Curie temperature T_C) and proximity mediated interactions between neighboring grains (through potential barriers created by thin layers of non-magnetic graphite) with energy J_t=exp(-d/s)J=5.8meV (which defines the intergranular Curie temperature T_{Ct}) with d=1.5nm and s=2nm being the intergranular distance and characteristic length, respectively

Fast Synthetic Dataset for Kitchen Object Segmentation in Deep Learning

Object recognition has been widely investigated in computer vision for many years. Currently, this process is carried out through neural networks, but there are very few public datasets available with mask and class labels of the objects for the training process in usual applications. In this paper, we address the problem of fast generation of synthetic datasets to train neural models because creating a handcraft labeled dataset with object segmentation is a very tedious and time-consuming task. We propose an efficient method to generate a synthetic labeled dataset that adequately combines background images with foreground segmented objects. The synthetic images can be created automatically with random positioning of the objects or, alternatively, the method can produce realistic images by keeping the realism in the scales and positions of the objects. Then, we employ Mask-RCNN deep learning model, to detect and segment classes of kitchen objects using images. In the experimental evaluation, we study both synthetic datasets, automatic or realistic, and we compare the results. We analyze the performance with the most widely used indexes and check that the realistic synthetic dataset, quickly created through our method, can provide competitive results and accurately classify the different objects

The interpretation of the field angle dependence of the critical current in defect-engineered superconductors

We apply the vortex path model of critical currents to a comprehensive analysis of contemporary data on defect-engineered superconductors, showing that it provides a consistent and detailed interpretation of the experimental data for a diverse range of materials. We address the question of whether electron mass anisotropy plays a role of any consequence in determining the form of this data and conclude that it does not. By abandoning this false interpretation of the data, we are able to make significant progress in understanding the real origin of the observed behavior. In particular, we are able to explain a number of common features in the data including shoulders at intermediate angles, a uniform response over a wide angular range and the greater discrimination between individual defect populations at higher fields. We also correct several misconceptions including the idea that a peak in the angular dependence of the critical current is a necessary signature of strong correlated pinning, and conversely that the existence of such a peak implies the existence of correlated pinning aligned to the particular direction. The consistency of the vortex path model with the principle of maximum entropy is introduced.Comment: 14 pages, 7 figure

Underway spectrophotometry along the Atlantic Meridional Transect reveals high performance in satellite chlorophyll retrievals

This is the final version. Available on open access from Elsevier via the DOI in this recordTo evaluate the performance of ocean-colour retrievals of total chlorophyll-a concentration requires direct comparison with concomitant and co-located in situ data. For global comparisons, these in situ match-ups should be ideally representative of the distribution of total chlorophyll-a concentration in the global ocean. The oligotrophic gyres constitute the majority of oceanic water, yet are under-sampled due to their inaccessibility and under-represented in global in situ databases. The Atlantic Meridional Transect (AMT) is one of only a few programmes that consistently sample oligotrophic waters. In this paper, we used a spectrophotometer on two AMT cruises (AMT19 and AMT22) to continuously measure absorption by particles in the water of the ship's flow-through system. From these optical data continuous total chlorophyll-a concentrations were estimated with high precision and accuracy along each cruise and used to evaluate the performance of ocean-colour algorithms. We conducted the evaluation using level 3 binned ocean-colour products, and used the high spatial and temporal resolution of the underway system to maximise the number of match-ups on each cruise. Statistical comparisons show a significant improvement in the performance of satellite chlorophyll algorithms over previous studies, with root mean square errors on average less than half (~0.16 in log10 space) that reported previously using global datasets (~0.34 in log10 space). This improved performance is likely due to the use of continuous absorption-based chlorophyll estimates, that are highly accurate, sample spatial scales more comparable with satellite pixels, and minimise human errors. Previous comparisons might have reported higher errors due to regional biases in datasets and methodological inconsistencies between investigators. Furthermore, our comparison showed an underestimate in satellite chlorophyll at low concentrations in 2012 (AMT22), likely due to a small bias in satellite remote-sensing reflectance data. Our results highlight the benefits of using underway spectrophotometric systems for evaluating satellite ocean-colour data and underline the importance of maintaining in situ observatories that sample the oligotrophic gyres.NEODAASCMEMSNatural Environment Research Council (NERC

Development and operation of a pixel segmented liquid-filled linear array for radiotherapy quality assurance

A liquid isooctane (C$_{8}$H$_{18}$) filled ionization linear array for radiotherapy quality assurance has been designed, built and tested. The detector consists of 128 pixels, each of them with an area of 1.7 mm $\times$ 1.7 mm and a gap of 0.5 mm. The small pixel size makes the detector ideal for high gradient beam profiles like those present in Intensity Modulated Radiation Therapy (IMRT) and radiosurgery. As read-out electronics we use the X-Ray Data Acquisition System (XDAS) with the Xchip developed by the CCLRC. Studies concerning the collection efficiency dependence on the polarization voltage and on the dose rate have been made in order to optimize the device operation. In the first tests we have studied dose rate and energy dependences, and signal reproducibility. Dose rate dependence was found lower than 2.5 % up to 5 Gy min$^{-1}$, and energy dependence lower than 2.1 % up to 20 cm depth in solid water. Output factors and penumbras for several rectangular fields have been measured with the linear array and were compared with the results obtained with a 0.125 cm$^{3}$ air ionization chamber and radiographic film, respectively. Finally, we have acquired profiles for an IMRT field and for a virtual wedge. These profiles have also been compared with radiographic film measurements. All the comparisons show a good correspondence. Signal reproducibility was within a 2% during the test period (around three months). The device has proved its capability to verify on-line therapy beams with good spatial resolution and signal to noise ratio.Comment: 16 pages, 12 figures Submitted to Phys. Med. Bio

Animal board invited review: Opportunities and challenges in using GWP* to report the impact of ruminant livestock on global temperature change

Ruminant livestock is a large contributor of CH4 emissions globally. Assessing how this CH4 and other greenhouse gases (GHG) from livestock contribute to anthropogenic climate change is key to understanding their role in achieving any temperature targets. The climate impacts of livestock, as well as other sectors or products/services, are generally expressed as CO2-equivalents using 100-year Global Warming Potentials (GWP100). However, the GWP100 cannot be used to translate emission pathways of short-lived climate pollutants (SLCPs) emissions to their temperature outcomes. A key limitation of handling long- and short-lived gases in the same manner is revealed in the context of any potential temperature stabilisation goals: to achieve this outcome, emissions of long-lived gases must decline to net-zero, but this is not the case for SLCPs. A recent alternative metric, GWP* (so-called ‘GWP-star’), has been proposed to overcome these concerns. GWP* allows for simple appraisals of warming over time for emission series of different GHGs that may not be obvious if using pulse-emission metrics (i.e. GWP100). In this article, we explore some of the strengths and limitations of GWP* for reporting the contribution of ruminant livestock systems to global temperature change. A number of case studies are used to illustrate the potential use of the GWP* metric to, for example, understand the current contribution of different ruminant livestock production systems to global warming, appraise how different production systems or mitigations compare (having a temporal element), and seeing how possible emission pathways driven by changes in production, emissions intensity and gas composition show different impacts over time. We suggest that for some contexts, particularly if trying to directly infer contributions to additional warming, GWP* or similar approaches can provide important insight that would not be gained from conventional GWP100 reporting. © 2023This research is supported by María de Maeztu excellence accreditation 2018-2022 (Ref. MDM-2017-0714), funded by MCIN/AEI/10.13039/501100011033/; and by the Basque Government through the BERC 2022-2025 program. Agustin del Prado is financed by the programme Ramon y Cajal from the Spanish Ministry of Economy, Industry and Competitiveness (RYC-2017-22143) and Ikerbasque. JL acknowledges funding from Wellcome Trust, Our Planet Our Health (Livestock, Environment and People—LEAP), award number 205212/Z/16/Z. FM and SH are funded by the California Air Resources Board (CARB35C10_18ISD025